SPSS

Same Statistical Models, Different (and Confusing) Output Terms

Learning how to analyze data can be frustrating at times. Why do statistical software companies have to add to our confusion?

I do not have a good answer to that question. What I will do is show examples. In upcoming blog posts, I will explain what each output means and how they are used in a model.

We will focus on ANOVA and linear regression models using SPSS and Stata software. As you will see, the biggest differences are not across software, but across procedures in the same software.

Member Training: What’s the Best Statistical Package for You?

by guest contributer

Choosing statistical software is part of The Fundamentals of Statistical Skill and is necessary to learning a second software (something we recommend to anyone progressing from Stage 2 to Stage 3 and beyond).

You have many choices for software to analyze your data: R, SAS, SPSS, and Stata, among others. They are all quite good, but each has its own unique strengths and weaknesses.

Interpreting Interactions in Linear Regression: When SPSS and Stata Disagree, Which is Right?

by Jeff Meyer Leave a Comment

Sometimes what is most tricky about understanding your regression output is knowing exactly what your software is presenting to you.

Here’s a great example of what looks like two completely different model results from SPSS and Stata that in reality, agree.

The Model

I ran a linear model regressing “physical composite score” on education and “mental composite score”.

The outcome variable, physical composite score, is a measurement of one’s physical well-being. The predictor “education” is categorical with four categories. The other predictor, mental composite score, is continuous and measures one’s mental well-being.

I am interested in determining whether the association between physical composite score and mental composite score is different among the four levels of education. To determine this I included an interaction between mental composite score and education.

The SPSS Regression Output

Here is the result of the regression using SPSS:

Tricks for Using Word to Make Statistical Syntax Easier

by Karen Grace-Martin 2 Comments

We’ve talked a lot around here about the reasons to use syntax — not only menus — in your statistical analyses.

Regardless of which software you use, the syntax file is pretty much always a text file. This is true for R, SPSS, SAS, Stata — just about all of them.

This is important because it means you can use an unlikely tool to help you code: Microsoft Word.

I know what you’re thinking. Word? Really?

Yep, it’s true. Essentially it’s because Word has much better Search-and-Replace options than your stat software’s editor.

Here are a couple features of Word’s search-and-replace that I use to help me code faster:

Mixed Models: Can you specify a predictor as both fixed and random?

by Karen Grace-Martin 20 Comments

One of the most confusing things about mixed models arises from the way it’s coded in most statistical software. Of the ones I’ve used, only HLM sets it up differently and so this doesn’t apply.

But for the rest of them—SPSS, SAS, R’s lme and lmer, and Stata, the basic syntax requires the same pieces of information.

1. The dependent variable

2. The predictor variables for which to calculate fixed effects and whether those [Read more…] about Mixed Models: Can you specify a predictor as both fixed and random?

How to Get SPSS GENLINMIXED Output Without the Model Viewer

by Karen Grace-Martin 12 Comments

I love working with my clients.

I love working with my clients for many reasons, but one of them is I learn so much from them.

Just this week, one of my clients showed me how to get SPSS GENLINMIXED results without the Model Viewer.

She’s my new hero.

If you’ve ever used GENLINMIXED, the procedure for Generalized Linear Mixed Models, you know that the results automatically appear in this new Model Viewer. [Read more…] about How to Get SPSS GENLINMIXED Output Without the Model Viewer